Chatbot Artificial Intelligence for Genetic Cancer Risk Assessment and Counseling: A Systematic Review and Meta-Analysis

Author:

Webster Emily M.1ORCID,Ahsan Muhammad Danyal1ORCID,Perez Luiza1ORCID,Levi Sarah R.1,Thomas Charlene1ORCID,Christos Paul1,Hickner Andy1ORCID,Hamilton Jada G.2ORCID,Babagbemi Kemi1,Cantillo Evelyn1ORCID,Holcomb Kevin1ORCID,Chapman-Davis Eloise1,Sharaf Ravi N.1ORCID,Frey Melissa K.1ORCID

Affiliation:

1. Weill Cornell Medicine, New York, NY

2. Memorial Sloan Kettering Cancer Center, New York, NY

Abstract

PURPOSE Most individuals with a hereditary cancer syndrome are unaware of their genetic status due to underutilization of hereditary cancer risk assessment. Chatbots, or programs that use artificial intelligence to simulate conversation, have emerged as a promising tool in health care and, more recently, as a potential tool for genetic cancer risk assessment and counseling. Here, we evaluated the existing literature on the use of chatbots in genetic cancer risk assessment and counseling. METHODS A systematic review was conducted using key electronic databases to identify studies which use chatbots for genetic cancer risk assessment and counseling. Eligible studies were further subjected to meta-analysis. RESULTS Seven studies met inclusion criteria, evaluating five distinct chatbots. Three studies evaluated a chatbot that could perform genetic cancer risk assessment, one study evaluated a chatbot that offered patient counseling, and three studies included both functions. The pooled estimated completion rate for the genetic cancer risk assessment was 36.7% (95% CI, 14.8 to 65.9). Two studies included comprehensive patient characteristics, and none involved a comparison group. Chatbots varied as to the involvement of a health care provider in the process of risk assessment and counseling. CONCLUSION Chatbots have been used to streamline genetic cancer risk assessment and counseling and hold promise for reducing barriers to genetic services. Data regarding user and nonuser characteristics are lacking, as are data regarding comparative effectiveness to usual care. Future research may consider the impact of chatbots on equitable access to genetic services.

Publisher

American Society of Clinical Oncology (ASCO)

Subject

General Medicine

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